Word2vec (Japanese Wikipedia)

Analysis of information sources in references of the Wikipedia article "Word2vec" in Japanese language version.

refsWebsite

Global rank Japanese rank

7nih.gov

4^th place

24^th place

6arxiv.org

69^th place

227^th place

5doi.org

2^nd place

6^th place

2harvard.edu

18^th place

107^th place

2aclweb.org

low place

1youtube.com

9^th place

8^th place

1code.google.com

4,942^nd place

6,718^th place

1groups.google.com

1,518^th place

2,822^nd place

1mit.edu

415^th place

1,150^th place

1medium.com

551^st place

1,605^th place

1github.com

383^rd place

521^st place

1deeplearning4j.org

low place

1radimrehurek.com

low place

aclweb.org

Levy, Omer; Goldberg, Yoav; Dagan, Ido (2015). “Improving Distributional Similarity with Lessons Learned from Word Embeddings”. Transactions of the Association for Computational Linguistics (Transactions of the Association for Computational Linguistics) 3: 211–225. doi:10.1162/tacl_a_00134.
Arora, S (Summer 2016). “A Latent Variable Model Approach to PMI-based Word Embeddings”. Transactions of Assoc. Of Comp. Linguistics 4: 385–399. doi:10.1162/tacl_a_00106. http://aclweb.org/anthology/Q16-1028.

arxiv.org

Mikolov, Tomas. "Efficient Estimation of Word Representations in Vector Space". arXiv:1301.3781 [cs.CL]。
Goldberg, Yoav; Levy, Omer. "word2vec Explained: Deriving Mikolov et al.'s Negative-Sampling Word-Embedding Method". arXiv:1402.3722 [cs.CL]。
Le, Quoc. "Distributed Representations of Sentences and Documents". arXiv:1405.4053 [cs.CL]。
Asgari, Ehsaneddin; Mofrad, Mohammad R.K. (2015). “Continuous Distributed Representation of Biological Sequences for Deep Proteomics and Genomics”. PLOS One 10 (11): e0141287. arXiv:1503.05140. Bibcode: 2015PLoSO..1041287A. doi:10.1371/journal.pone.0141287. PMC 4640716. PMID 26555596.
Ng, Patrick (2017). "dna2vec: Consistent vector representations of variable-length k-mers". arXiv:1701.06279 [q-bio.QM]。
Altszyler, E.; Ribeiro, S.; Sigman, M.; Fernández Slezak, D. (2017). “The interpretation of dream meaning: Resolving ambiguity using Latent Semantic Analysis in a small corpus of text”. Consciousness and Cognition 56: 178–187. arXiv:1610.01520. doi:10.1016/j.concog.2017.09.004. PMID 28943127.

code.google.com

“Google Code Archive - Long-term storage for Google Code Project Hosting.”. code.google.com. 2016年6月13日閲覧。

deeplearning4j.org

“Doc2Vec and Paragraph Vectors for Classification”. 2016年1月13日閲覧。

doi.org

Asgari, Ehsaneddin; Mofrad, Mohammad R.K. (2015). “Continuous Distributed Representation of Biological Sequences for Deep Proteomics and Genomics”. PLOS One 10 (11): e0141287. arXiv:1503.05140. Bibcode: 2015PLoSO..1041287A. doi:10.1371/journal.pone.0141287. PMC 4640716. PMID 26555596.
Banerjee, Imon; Chen, Matthew C.; Lungren, Matthew P.; Rubin, Daniel L. (2018). “Radiology report annotation using intelligent word embeddings: Applied to multi-institutional chest CT cohort”. Journal of Biomedical Informatics 77: 11–20. doi:10.1016/j.jbi.2017.11.012. PMC 5771955. PMID 29175548.
Levy, Omer; Goldberg, Yoav; Dagan, Ido (2015). “Improving Distributional Similarity with Lessons Learned from Word Embeddings”. Transactions of the Association for Computational Linguistics (Transactions of the Association for Computational Linguistics) 3: 211–225. doi:10.1162/tacl_a_00134.
Arora, S (Summer 2016). “A Latent Variable Model Approach to PMI-based Word Embeddings”. Transactions of Assoc. Of Comp. Linguistics 4: 385–399. doi:10.1162/tacl_a_00106. http://aclweb.org/anthology/Q16-1028.
Altszyler, E.; Ribeiro, S.; Sigman, M.; Fernández Slezak, D. (2017). “The interpretation of dream meaning: Resolving ambiguity using Latent Semantic Analysis in a small corpus of text”. Consciousness and Cognition 56: 178–187. arXiv:1610.01520. doi:10.1016/j.concog.2017.09.004. PMID 28943127.

github.com

“Doc2vec for IMDB sentiment analysis”. 2016年2月18日閲覧。

groups.google.com

“Parameter (hs & negative)”. Google Groups. 2016年6月13日閲覧。

harvard.edu

ui.adsabs.harvard.edu

Mikolov, Tomas; Sutskever, Ilya; Chen, Kai; Corrado, Greg S.; Dean, Jeff (2013). Distributed representations of words and phrases and their compositionality. Advances in Neural Information Processing Systems. Bibcode:2013arXiv1310.4546M。
Asgari, Ehsaneddin; Mofrad, Mohammad R.K. (2015). “Continuous Distributed Representation of Biological Sequences for Deep Proteomics and Genomics”. PLOS One 10 (11): e0141287. arXiv:1503.05140. Bibcode: 2015PLoSO..1041287A. doi:10.1371/journal.pone.0141287. PMC 4640716. PMID 26555596.

medium.com

“Doc2Vec tutorial using Gensim”. 2015年8月2日閲覧。

mit.edu

jmlr.csail.mit.edu

“Visualizing Data using t-SNE”. Journal of Machine Learning Research, 2008. Vol. 9, pg. 2595. 2017年3月18日閲覧。

nih.gov

radimrehurek.com

“Gensim - Deep learning with word2vec”. 10 June 2016閲覧。

youtube.com

Řehůřek, Radim. Word2vec and friends. 2015年8月14日閲覧。

Word2vec (Japanese Wikipedia)

aclweb.org

arxiv.org

code.google.com

deeplearning4j.org

doi.org

github.com

groups.google.com

harvard.edu

ui.adsabs.harvard.edu

medium.com

mit.edu

jmlr.csail.mit.edu

nih.gov

pubmed.ncbi.nlm.nih.gov

ncbi.nlm.nih.gov

pmc.ncbi.nlm.nih.gov

radimrehurek.com

youtube.com